Clarity in cloud chaos: Why your data strategy is the true MVP
In this episode of Unscrew Your Data Host Christian Kruk sheds light on the dilemma that we experience every day at ruhrdot: How do you choose “100,000 services and tools” What is the best cloud data platform? Is it Snowflake, Databricks, Microsoft Fabric, AWS, or Google?
His guest in this episode: Our data expert Alex Rabe. As co-founder of ruhrdot., Alex provides a clear and pragmatic answer to this confusion: Success is not decided by the tool. The true “machete in the data jungle” is data strategy.
Here we summarize the core topics of the insightful conversation that brings clarity to the world of cloud data platforms
The unavoidable cloud: The end of on-premise
In view of the “zoo” of tools, the initial reaction of many managing directors is often: Which tool do we buy? Alex Rabe disagrees with this thinking. Tool selection is irrelevant as long as there is no clear data strategy. As Alex puts it in a nutshell: “The strategy is the A&O when it really comes to making a long-term commitment to a platform. [...] Without a strategy, you won't get them to work regardless of the tool.”
According to Alex, a successful strategy must meet several criteria: It must Top-down be anchored in management, but at the same time Bottom-Up which specific needs from the specialist areas (Controlling, HR, Sales). A data warehouse or CDP (cloud data platform) belongs centrally in ITSince it is a holistic topic acts.
However, the biggest value of the strategy is filter effect. It defines which use cases you truly want (for example BI (business intelligence)) and which don't (for example machine learning). This reduces the potential tools to a manageable selection and prevents expensive incorrect purchases. Although buying a tool is a Quick-Win (measurable progress), but the strategy is discipline, which delivers medium-term and long-term business value.
The right CDP (Cloud Data Platform) for your use case: Rabes tool recommendations
Only after the strategy is the selection of the CDP (Cloud Data Platform). In the podcast, Alex Rabe gives clear recommendations, depending on where the strategic focus is:
- Pure BI (Business Intelligence) & Reporting: Here is Snowflake a clear recommendation based on easy learning curve and the sophisticated solution that is easy to integrate into existing hyperscalers.
- BI (Business Intelligence) + AI/ML (Machine Learning): The following applies here Databricks as a gold standard. It is an integrated platform that covers both cloud data warehouse and the entire machine learning stack. The learning curve is steeper here, but the versatility pays off.
- Strong Microsoft stack: For companies that are firmly anchored in the MS ecosystem, attracts Microsoft Fabric with strong integration (Power BI (Business Intelligence), MS Stack). However, care should be taken here, as the Capacity unit pricing and the lower maturity compared to Databricks require detailed analysis.
- Strong Google Stack: BigQuery is ideal for start-ups and scale-ups (for example in e-commerce) when the source systems are simple and the focus is on speed.
- Strong SAP stack: Die SAP Business Data Cloud (BDC) is a good first step towards opening up SAP, but our expert recommends it due to the high Vendor lock-ins only in very limited scenarios.
The A&O for the future
Christian Kruk and our data expert Alex Rabe agree: At the end of the day, almost any tool works, as long as you use the strategic base created. The real added value comes when controllers no longer struggle with Excel for three days, but have data of the right quality at the push of a button. Your next step: Don't start with the tool benchmark, define yours Data Strategy.
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